EP1840836A1 - Method of performing fast compression and decompression for image - Google Patents
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- 238000007906 compression Methods 0.000 title claims abstract description 37
- 230000006837 decompression Effects 0.000 title claims abstract description 36
- 230000006835 compression Effects 0.000 title claims abstract description 27
- 238000013144 data compression Methods 0.000 claims abstract description 6
- 238000013139 quantization Methods 0.000 claims description 28
- 230000009466 transformation Effects 0.000 claims description 8
- 238000012545 processing Methods 0.000 abstract description 8
- 239000011159 matrix material Substances 0.000 description 15
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- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
- H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
- H04N19/102—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or selection affected or controlled by the adaptive coding
- H04N19/12—Selection from among a plurality of transforms or standards, e.g. selection between discrete cosine transform [DCT] and sub-band transform or selection between H.263 and H.264
- H04N19/122—Selection of transform size, e.g. 8x8 or 2x4x8 DCT; Selection of sub-band transforms of varying structure or type
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- H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
- H04N19/134—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the element, parameter or criterion affecting or controlling the adaptive coding
- H04N19/136—Incoming video signal characteristics or properties
- H04N19/14—Coding unit complexity, e.g. amount of activity or edge presence estimation
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- H04N19/10—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding
- H04N19/169—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding
- H04N19/17—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object
- H04N19/176—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals using adaptive coding characterised by the coding unit, i.e. the structural portion or semantic portion of the video signal being the object or the subject of the adaptive coding the unit being an image region, e.g. an object the region being a block, e.g. a macroblock
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- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
- H04N19/00—Methods or arrangements for coding, decoding, compressing or decompressing digital video signals
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Abstract
Description
- The present invention relates to computer image processing and data compression technology, in particular to a process of accelerated image compression and decompression.
- Joint Photographic Experts Group (JPEG) is a committee under International Standard Organization (ISO) responsible for setting up the static image compression formats international standard which is widely used in the areas of image storage and digital cameras. JPEG proposes a number of processes for image compression and decompression based on the discrete cosine transform (DCT) and the inverse discrete cosine transform (IDCT).
- A known process of image compression based on the DCT comprises the following steps.
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Step 1 is a pre-processing step by inputting image data. The purpose of this step is to pre-process the input data so as to make the input data match the following steps, or so as to achieve desirable compression result. This step comprises splitting an original image data into a plurality of 8x8 blocks, standardizing the pixels of the input image, and performing a color space transformation, etc. - Step 2 is to perform the DCT. The input of this step is 8x8 image data blocks, wherein all the values of pixels are standardized. The equation for the DCT is:
wherein:
u, v, x, y = 0, 1,2.......7;
(x, y) represents the coordinate of a point within a block before the DCT, where (0,0) is the coordinate of the pixel on the top left corner of a block; f(x, y) is the value of the pixel at the coordinate (x, y) before the DCT; (u, v) is the coordinate of the pixel after the DCT; F(u, v) is the value of the pixel at the coordinate (u, v) after the DCT.
as u, v = 0, C(u), C(v)=1/sqrt(2), where sqrt means the square root calculation. - Step 3 is to perform quantization. The input of this step is the data block after the DCT and a designated quantization matrix. All elements in the quantization matrix are non-zero positive integrals. Assuming that the quantization matrix is Q(x, y), the quantization is conducted according to the following equation:
- Step 4 is to perform one dimensional prediction of a direct current (DC) coefficient. F (0, 0) is called as a DC coefficient, and the other elements are known as Alternating Current (AC) coefficients. To process the DC coefficient, assuming P is the DC coefficient of a preceding image block, which is also the prediction value of the current DC coefficient, the equation for prediction is shown as below:
F (0, 0) = F (0, 0)-P; // the value of DC coefficient after prediction
The predicted value of the DC coefficient for the next image block becomes:
P = P + F (0, 0); // the value of DC coefficient predicted for the next image block. - Step 5 is to perform DC Entropy coding. The input of this step is the DC coefficient in the matrix which is the output of step 4. The black element on the top left corner of Figure 2 represents the DC coefficient.
- Step 6 is to perform an AC Entropy coding, the input of which are the AC coefficients in the outputting matrix of step 4, wherein AC coefficients are arranged in "zigzag"order and a run-length encoding algorithm for entropy coding is employed, referring to Figure 2. Besides the black element on the top left corner of the data block, the rest of elements in Figure 2 are AC coefficients. The bending line indicates AC coefficients being encoded in a zigzag manner. Figure 3 is flow chart for showing the AC coefficient entropy run length coding process.
- Decompression based on the IDCT, which is the reverse of the compression, is described below.
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Step 1 is to perform DC coefficient entropy decoding. - Step 2 is to perform AC coefficients entropy decoding.
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- Step 6 is a post-processing step, which is a reverse of the pre-processing.
- Figure 1 shows a flowchart of JPEG compression/decompression process based on the DCT and the IDCT. Details of JPEG is disclosed by the International Telegraph and Telephone Consultative Committee (CCITT) in the document with reference number CCITT Rec.T.81(1992E) with the title "Information Technology-Digital Compression and Coding of Continuous-Tone Still Images-Requirement and Guideline".
- Currently, the JPEG compression process based on the DCT is able to provide an acceptable compression rate. Moreover, when a compressed image is decompressed, the difference between the original image and the decompressed one is hard to be detectable visually. But, its processing speed is not good. It is obvious from the equations for the DCT and the IDCT that a heavy load of calculation is required. Although a lot of accelerated processes are proposed to reduce the work load of calculation, those known accelerated processes cannot be applied to process those images with high resolution. And, the processing speed is still one major obstacle for JPEG applications.
- In order to overcome the shortcomings in the prior art, the objective of present invention is to increase the processing speed of JPEG compression/decompression process based on the DCT and the IDCT without impacting the quality of the image.
- To achieve above mentioned objective, one aspect of present invention is to provide a process for image data compression, comprising the following steps:
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step 1 is to pre-process an input image, comprising splitting an original image data into a plurality of image data blocks, standardizing pixels of the image, and performing a color space transformation; - step 2 is to determine whether a given data block satisfies a requirement for an accelerated compression, wherein, if yes, step 3 is carried out, otherwise step 4 is carried out; and wherein the requirement is satisfied when all pixel values in one image block are equal;
- step 3 is to perform a simplified DCT on the image data block and go to step 5;
- step 4 is to perform a DCT on the image data block;
- step 5 is to quantify a resulting data block after its DCT;
- step 6 is to perform one dimensional prediction on a DC coefficient of the data block;
- step 7 is to perform DC entropy coding on the DC coefficient of the data block; and
- step 8 is to perform AC entropy coding on AC coefficients of the data block, and end the process.
- Further, to improve the compression process, the determination of the above step 2 could be further improved by combing a number of image data into a "unit" for comparison, rather than one image datum at one time.
- Further, if the requirement is satisfied, the DCT and the quantization are merged to form a simple DCT-quantization process, the DC entropy coding and the AC entropy coding are merged to form a simple entropy coding process, a preferred workflow for accelerated compression is listed below:
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step 1 is to pre-process the inputted image; - step 2 is to determine whether the given data block satisfies the requirement, if yes, step 8 is carried out, otherwise step 4 is carried out, wherein the requirement is satisfied when all pixel values in an image block are equal;
- step 3 is to perform the DCT on the image data block;
- step 4 is to quantify the resulting data block after its DCT;
- step 5 is to perform one dimensional prediction on the DC coefficient of the data block;
- step 6 is to perform the DC entropy coding on the DC coefficient of the data block;
- step 7 is to perform the AC entropy coding on the AC coefficients of the data block;
- step 8 is to perform the simplified DCT-quantization process;
- step 9 is to perform one dimensional prediction on the DC coefficient of the data block; and
- step 10 is to perform the simple entropy coding, and end the process.
- The present invention also provides a process for image data decompression, compriseing the following steps:
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step 1 is to input a compressed image data block, performing a DC coefficient entropy decoding on the image data block; - step 2 is to perform a AC coefficients entropy decoding;
- step 3 is to perform one dimensional inverse prediction on a DC coefficient of the image data block;
- step 4 is to perform a inverse quantization on a quantified image data block;
- step 5 is to determine whether a given image data block satisfies a first requirement of an accelerated decoding process, if yes, step 6 is carried out, otherwise, step 7 is carried out, wherein the first requirement is that all the AC coefficients in the given image data block equals to zero;
- step 6 is to perform a simplified DCT, then step 8 is carried out;
- step 7 is to perform a DCT; and
- step 8 is to post-process the image data and output image data that have been decompressed.
- Further, to improve the decompression process, the step 5 in the decompression process is further improved by combining a number of image data into a "unit", and performing a comparison in view of the unit, rather than one datum by one datum.
- Still further, when the image data is decompressed, a start point of the accelerated process is forwarded, and wherein if a second requirement for the accelerated decompression is satisfied, the AC entropy decoding process is omitted, and the inverse quantization and DCT process both are simplified, wherein a preferred workflow for the accelerated decompression is listed below:
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step 1 is to perform DC entropy decoding on the DC coefficients in the image data block. - step 2 is to determine whether the image data block satisfies a second requirement for the accelerated decompression process, if yes, step 7 is carried out, otherwise step 3 is carried out, wherein the second requirement is that a first coded AC coefficient is an end code such as End of Block,;
- step 3 is to perform the entropy decoding on the AC coefficients in the image data block;
- step 4 is to perform one dimensional inverse prediction on the DC coefficient in the image data block;
- step 5 is to perform the inverse quantization;
- step 6 is to perform an IDCT, and go to step 9 after the IDCT is completed;
- step 7 is to perform one dimensional inverse prediction on the DC coefficient in the image data block;
- step 8 is to perform a simple IDCT-inverse quantization process; and
- step 9 is to post-process the image data and output a decompressed image data.
- The present invention could accelerate the processing speed of JPEG compression/decompression based on the DCT and the IDCT, without impacting the quality of an image and without increasing the time length for the process.
- Figure 1 is a flow chart for a typical JPEG compression/decompression process based on the DCT and the IDCT;
- Figure 2 is a layout view for the zigzag AC coefficients;
- Figure 3 is a flow chart for AC coefficients entropy run length coding;
- Figure 4 is a work chart of an accelerated JPEG compression/decompression process; and
- Figure 5 shows a flow chart of a preferable accelerated JPEG compression/decompression process.
- The invention will be now described herein with reference to embodiments and drawings.
- Figures 4 and 5 show a basic accelerated JPEG compression process based on the DCT.
- Specifically,
step 1 is to pre-process an input image, including splitting the input image data into a plurality of image data blocks, standardizing values of pixels of the image, and conducting a color space transformation. - Step 2 is to determine whether a given image block satisfies with the requirement for accelerated compression. If yes, the procedure goes to step 3, otherwise, goes to step 4. The input of this step is a plurality of 8x8 image data blocks. And, all the values of pixels have been standardized. The mentioned requirement is that all the values of pixels in one image block are equal. JPEG can process both 8 bits and 12 bits of pixel depths according to the following pseudo-codes:
For 8 bits pixel depth: for (int n=1; n<64; n++) if (f[0]!=f[n]) return false; return true;In the worst case, the above needs 63 comparisons.
For 12 bits pixel depth: int tmp=read_bit(f,12); // read 12 bits from the data stream for (int n=1; n<64; n++) if(read(f,12)!=tmp) return false; return true;wherein f represents a data stream. The worst case for the above operation is to perform 64 iterations and 63 comparisons. The return value "true" means the satisfaction of the requirement, while the return value "false" means the dissatisfaction of the requirement.
unsigned int*p = (unsigned int*)f; unsigned int temp = circle_left_shift(p[0],8); // circle to the left by shifting 8 bits (of course, it would work as well if shifting to the right by 8 bits); for ( int n = 0; n<64/sizeof(int); n++) if(temp ! = p[n]) return false return true;
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step 1 is to pre-process, which is conducted identically to the step of pre-processing in the background portion; - step 2 is to determine whether a given image data block satisfies with a requirement of the accelerated compression. If yes, the procedure goes to step 8, otherwise to step 3; wherein the said requirement of accelerated compression is the same as the requirement mentioned in step 2 of the basic process. The determination of satisfaction of the requirement could be done according to the above step 2 as well as the improved step 2;
- step 3 is to perform the DCT as mentioned in the background portion;
- step 4 is to perform the quantization process as mentioned in the background portion;
- step 5 is to perform one dimensional prediction one DC coefficient as mentioned in the background portion;
- step 6 is to perform DC coefficient entropy coding as mentioned in the background portion;
- step 7 is to perform AC coefficients entropy coding as mentioned in the background portion;
- step 8 is to perform a simplified DCT-quantization process, wherein assuming F is a matrix before the process, f represents a matrix after the transformation, Q is a
quantization matrix - step 9 is to perform one dimensional prediction on the DC coefficient as mentioned in the background portion; and
- step 10 is to simplify the entropy coding and ending the procedure, wherein
- the entropy coding only needs to perform twice as below:
DC_code(F(0,0)); //DC entropy coding for DC coefficient after prediction
AC_code(EOB); //code word for ending the encoding.
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step 1 is to perform a DC coefficient decoding as mentioned in the background; - step 2 is to perform AC coefficients decoding as mentioned in the background;
- step 3 is to perform one dimensional DC coefficient inverse prediction as mentioned in the background;
- step 4 is to perform the inverse quantization as mentioned in the background;
- step 5 is to determine whether a given image block satisfies with the first requirement of accelerated decompression. If yes, the procedure goes to step 6, otherwise to step 7; wherein the input of this step is a data block of 64 bits including AC and DC coefficients; the first requirement is that all AC coefficients in the input data block equals to zero. The following is the pseudo-code that determines whether the first requirement of accelerated decompression is satisfied. Assuming that F is the inputted data block,
for ( int n =1 ; n<64; n++) if (F[0]!=0) return false; //the requirement is not satisfied return true //the requirement is satisfiedin the worst case, 63 iterations in above pseudo-code are needed;
- step 6 is to perform a simplified the IDCT and then proceeding to step 8, wherein the performing is conducted according to an equation as follows: assume F(x, y) represents a matrix before the IDCT, and f(x, y) represents a matrix after the IDCT, where x, y = 0, 1, 2 ...7,
f(x, y) = F(0, 0) /8, for x, y = 0, 1, 2...7; - step 7 is to perform the IDCT as mentioned in the background; and
- step 8 is to perform the post-processing as mentioned in the background.
unsigned int temp = F[0]; // storing DC coefficient F[0]=0; //clearing DC coefficient unsigned int*p = (unsigned int*)(&F(0, 0)); for (int n=0, n<64*sizeof(short)/sizeof(int); n++) if (p[n]!=0) { F[0]=temp; Return false;//the requirement is not satisfied } F[0] = temp; Return true; //the requirement is satisfied
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step 1 is to perform DC coefficient entropy decoding as mentioned in the background; - step 2 is to determine whether a given image data block satisfies with the second requirement of accelerated decompression, and if yes, the procedure goes to step 7, otherwise, goes to step 3; wherein the second requirement is that the first AC coefficients entropy coding is the flag of end of the block with the following pseudo-code:
R = DECODE (); //decoding the first encoded AC coefficient
if ( R == EOB) //checking if it is the flag of end of the block
return true; // the requirement is satisfied
return false; // the requirement is not satisfied it is noted that, when the second requirement is satisfied, the AC coefficients entropy decoding will be omitted; - step 3 is to perform AC coefficients entropy decoding as mentioned in the background;
- step 4 is to perform one dimensional inverse DC coefficient prediction as mentioned in the background;
- step 5 is to perform the inverse quantization as mentioned in the background;
- step 6 is to perform the IDCT and then proceed to step 9 as mentioned in the background;
- step 7 is to perform one dimensional DC coefficient inverse prediction as mentioned in the background;
- step 8 is to perform a simplified the IDCT-quantization process, wherein, assuming that F represents a matrix before the transformation, f represents a matrix after the transformation, and Q represents a quantization matrix,
F(x, y) = F(0, 0) *(Q(0, 0)/8), for x, y = 0, 1, 2...7.
Note Q(0, 0) is a constant; and - step 9 is to perform the post-processing as mentioned in the background.
Claims (6)
- A process for image data compression, comprising the following steps:step 1 is to pre-process an input image, comprising splitting an original image data into a plurality of image data blocks, standardizing pixels of the image, and performing a color space transformation;step 2 is to determine whether a given data block satisfies a requirement for an accelerated compression, wherein, if yes, step 3 is carried out, otherwise step 4 is carried out; and wherein the requirement is satisfied when all pixel values in one image block are equal;step 3 is to perform a simplified DCT on the image data block and go to step 5;step 4 is to perform a DCT on the image data block;step 5 is to quantify a resulting data block after its DCT;step 6 is to perform one dimensional prediction on a DC coefficient of the data block;step 7 is to perform DC entropy coding on the DC coefficient of the data block; andstep 8 is to perform AC entropy coding on AC coefficients of the data block, and end the process.
- The process for image data compression according to claim 1, wherein the step 2 is further improved by combining a number of image data into a "unit" and performing a comparison in view of the unit, rather than one datum by one datum.
- The process for image data compression according to claim 1 or 2, wherein if the requirement is satisfied, the step of performing the DCT and the step for quantifying are merged to one step of performing a simplified DCT-quantization process; and the step of performing the DC entropy coding and performing the AC entropy coding are merged to form a simplified entropy coding, a preferred workflow for accelerated compression is listed below:step 1 is to pre-process the inputted image;step 2 is to determine whether the given data block satisfies the requirement, if yes, step 8 is carried out, otherwise step 4 is carried out, wherein the requirement is satisfied when all pixel values in an image block are equal;step 3 is to perform the DCT on the image data block;step 4 is to quantify the resulting data block after its DCT;step 5 is to perform one dimensional prediction on the DC coefficient of the data block;step 6 is to perform the DC entropy coding on the DC coefficient of the data block;step 7 is to perform the AC entropy coding on the AC coefficients of the data block;step 8 is to perform the simplified DCT-quantization process;step 9 is to perform one dimensional prediction on the DC coefficient of the data block; andstep 10 is to perform the simple entropy coding, and end the process.
- A process for image data decompression, comprising the following steps:step 1 is to input a compressed image data block, performing a DC coefficient entropy decoding on the image data block;step 2 is to perform a AC coefficients entropy decoding;step 3 is to perform one dimensional inverse prediction on a DC coefficient of the image data block;step 4 is to perform a inverse quantization on a quantified image data block;step 5 is to determine whether a given image data block satisfies a first requirement of an accelerated decoding process, if yes, step 6 is carried out, otherwise, step 7 is carried out, wherein the first requirement is that all the AC coefficients in the given image data block equals to zero;step 6 is to perform a simplified DCT, then step 8 is carried out;step 7 is to perform a DCT; andstep 8 is to post-process the image data and output image data that have been decompressed.
- The process for image data decompression according to claim 4, wherein the step 5 is further improved by combining a number of image data into a "unit", and performing a comparison in view of the unit, rather than one datum by one datum.
- The process for image data decompression according to claim 4, wherein when the image data is decompressed, a start point of the accelerated process is forwarded, and wherein if a second requirement for the accelerated decompression is satisfied, the AC entropy decoding process is omitted, and the inverse quantization and DCT process both are simplified, wherein a preferred workflow for the accelerated decompression is listed below:step 1 is to perform DC entropy decoding on the DC coefficients in the image data block.step 2 is to determine whether the image data block satisfies a second requirement for the accelerated decompression process, if yes, step 7 is carried out, otherwise step 3 is carried out, wherein the second requirement is that a first coded AC coefficient is an end code such as End of Block,;step 3 is to perform the entropy decoding on the AC coefficients in the image data block;step 4 is to perform one dimensional inverse prediction on the DC coefficient in the image data block;step 5 is to perform the inverse quantization;step 6 is to perform an IDCT, and go to step 9 after the IDCT is completed;step 7 is to perform one dimensional inverse prediction on the DC coefficient in the image data block;step 8 is to perform a simple IDCT-inverse quantization process; andstep 9 is to post-process the image data and output a decompressed image data.
Applications Claiming Priority (2)
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CNB2005100005896A CN1282107C (en) | 2005-01-07 | 2005-01-07 | Method for rapidly compressing and decompressing image |
PCT/CN2005/002292 WO2006072206A1 (en) | 2005-01-07 | 2005-12-23 | Method of performing fast compression and decompression for image |
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EP1840836A4 EP1840836A4 (en) | 2009-03-04 |
EP1840836B1 EP1840836B1 (en) | 2012-01-25 |
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EP (1) | EP1840836B1 (en) |
JP (1) | JP4831547B2 (en) |
CN (1) | CN1282107C (en) |
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CN103413287B (en) * | 2013-08-27 | 2016-09-14 | 浙江宇视科技有限公司 | A kind of JPEG picture synthetic method and device |
KR102285940B1 (en) | 2015-05-29 | 2021-08-05 | 에스케이하이닉스 주식회사 | Data processing circuit, data storage device comprising data processing circuit and operating method thereof |
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US11177835B2 (en) | 2015-09-25 | 2021-11-16 | SK Hynix Inc. | Data storage device |
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2005
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- 2005-12-23 US US11/813,388 patent/US8548266B2/en active Active
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Also Published As
Publication number | Publication date |
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CN1282107C (en) | 2006-10-25 |
JP4831547B2 (en) | 2011-12-07 |
CN1622137A (en) | 2005-06-01 |
EP1840836A4 (en) | 2009-03-04 |
US20090016629A1 (en) | 2009-01-15 |
ATE543338T1 (en) | 2012-02-15 |
EP1840836B1 (en) | 2012-01-25 |
US8548266B2 (en) | 2013-10-01 |
WO2006072206A1 (en) | 2006-07-13 |
JP2008527809A (en) | 2008-07-24 |
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